Falah/deep_learning_books_dataset
Deep Learning Books Dataset Dataset Information Features: page_no: Integer (int64) - Page number in the book. page_content: String - Text content of the page. Splits: train: Training split. Number of examples: 474 Number of bytes: 1,030,431 Download Size: 509,839 bytes Dataset Size: 1,030,431 bytes Dataset Application This dataset "deep_learning_books_dataset" contains text data from various pages of books related to deep learning. It… See the full description on the dataset page: https://huggingface.co/datasets/Falah/deep_learning_books_dataset.
Deep Learning Books Dataset
Dataset Information
- Features:
page_no: Integer (int64) - Page number in the book.page_content: String - Text content of the page.
- Splits:
train: Training split.- Number of examples: 474
- Number of bytes: 1,030,431
- Download Size: 509,839 bytes
- Dataset Size: 1,030,431 bytes
Dataset Application
This dataset "deeplearningbooks_dataset" contains text data from various pages of books related to deep learning. It can be used for various natural language processing (NLP) tasks such as text classification, language modeling, text generation, and more.
Using Python and Hugging Face's Transformers Library
To use this dataset for NLP text generation and language modeling tasks, you can follow these steps:
- Install the required libraries:
pip install datasets
from datasets import load_dataset
dataset = load_dataset("Falah/deep_learning_books_dataset")
Citation
Please use the following citation when referencing this dataset:
@dataset{deep_learning_books_dataset,
author = {Falah.G.Salieh},
title = {Deep Learning Books Dataset,},
year = {2023},
publisher = {HuggingFace Hub},
version = {1.0},
location = {Online},
url = {https://huggingface.co/datasets/Falah/deep_learning_books_dataset}
}
### Apache License: The "{Deep Learning Books Dataset" is distributed under the Apache License 2.0. The specific licensing and usage terms for this dataset can be found in the dataset repository or documentation. Please make sure to review and comply with the applicable license and usage terms before downloading and using the dataset.
